Surveillance of enteric viruses in bivalves from Ecuador during the year 2021

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Hasing, Pablo Endara, Juan Daniel Mosquera, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9296080/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Food-related illnesses remain a major health concern worldwide, and more than one-fifth of them can be attributed to enteric viruses. Bivalve mollusks are recognized vectors due to their ability to concentrate pathogens and toxins present in the surrounding water of the environment in which they live, and because they are consumed raw or undercooked. In Ecuador, food contamination with viruses is a little explored area. Furthermore, only a small percentage of wastewater is treated before being discharged into the sea. Therefore, this descriptive study aimed to determine the presence of five enteric viruses in bivalves (mainly black shellfish) during the second semester of 2021. We analyzed 98 samples of bivalves from markets in 8 continental Ecuadorian cities and 3 wild mangrove oysters from Galapagos Islands using qRT-PCR to detect the enteric viruses: Norovirus genogroups I and II, human Adenovirus serotypes 40 and 41, Rotavirus A, human Astrovirus, and Sapovirus. At least one virus was detected in 69.3% of the samples, and 38.6% showed contamination with a single virus. Adenovirus was the most common (49.5%), followed by Norovirus genogroup I (20.8%). Two viruses were co-detected in 19.8% of the samples, being Rotavirus-Adenovirus the most common combination. Three viruses were detected in 8.9% of the samples. Seasonality was observed for adenovirus, with an increased detection occurring during the dry season. Our findings demonstrate the presence of genetic material of human viruses in Ecuadorian bivalves during 2021, reflecting viral circulation within our population and a potential health risk that should be addressed. Enteric viruses bivalve Norovirus Rotavirus Adenovirus Figures Figure 1 Introduction According to the latest global estimates, there are at least 600 million cases of foodborne diseases (FBDs) annually resulting in 420,000 deaths (WHO, 2015), with Norovirus (NoV) being the leading agent of foodborne disease cases also accounting for a high mortality burden (35 000 foodborne associated deaths globally) (Goyal & Cannon, 2016 ). In addition to NoV, human Adenovirus (HAdV), Astrovirus (HAstV), Sapovirus (SaV), and Rotavirus (RV) have also been described as agents of food and waterborne diseases (Goyal & Cannon, 2016 ). Except for HAdV, the other four enteric viruses are included in the list of 31 major foodborne pathogens identified by the CDC (Scallan et al., 2011 ). Contamination of water and food, which contributes to the fecal-oral transmission of enteric viruses, is facilitated by the low number of viral particles capable of causing human infection (18 for NoV), the high number of viruses shed in feces (up to 10 10 per gram), and the viral stability in the environment (Goyal & Cannon, 2016 ). Viral contamination of food can occur at two different stages of food production: preharvest or postharvest. Preharvest contamination results from environmental contamination associated with wastewater and it is common for seafood and vegetables. Postharvest contamination is common for ready-to-eat foods, and it is associated with bad hygiene practices (Bosch et al., 2018 ). Bivalve shellfish have been widely described as reservoirs and vectors of human pathogens and are responsible for more than 60% of foodborne outbreaks worldwide (Butt, Aldridge, & Sander, 2004 ; Butt, Aldridge, & Sanders, 2004 ). This fact can be attributed to their feeding mechanism through filtration which allows them to concentrate pathogens from the surrounding water (Yang et al., 2022 ). A long list of microorganisms such as viruses (including human calicivirus NoV and HAstV, and hepatitis A virus, hepatitis E virus, RV, HAdV, enterovirus) (Lees, 2000 ); bacteria ( Vibrio spp., Salmonella spp., E. coli Shigellae, Aeromonas spp., Plesiomonas spp.) and parasites (both protozoa and helminths), are transmitted to humans by ingesting contaminated raw shellfish (Butt, Aldridge, & Sander, 2004 ; Butt, Aldridge, & Sanders, 2004 ); which can be an important issue in Ecuador because raw or undercooked shellfish is consumed frequently (Orden-Mejía et al., 2021 ). Viral FBDs are at the top of the food safety priorities established in the EU (Rowe & Bolger, 2016 ). In addition, the development of policies and programs to strengthen food safety is encouraged by the WHO (WHO, 2015), and assessment and control of foodborne pathogens is one of the key issues (Bosch et al., 2018 ). Ecuador surveillance focuses on limited pathogens considering only Salmonella spp., E. coli Shigellae, and hepatitis A virus (HAV) for mandatory reporting, even though these agents represent only a quarter of the FBD cases identified (MSP, 2025 ). During 2024, 13 959 cases of FBDs were documented; and 10 799 were categorized as “other food poisoning” without specifying the etiological agent (MSP, 2025 ). This illustrates the limited characterizing of FBD agents in Ecuador, where only a few studies have described viruses in food, including the detection of noroviruses and HAV in strawberries and spinach (Salazar et al., 2023 ). This highlights the need to strengthen surveillance and tools to identify the specific pathogens circulating in our country responsible for this important burden, allowing us to better characterize the local epidemiology. On the other hand, E. coli count has been widely used as a marker for fecal contamination of food assessing their safety for human consumption (Devane et al., 2020 ), however, viruses have been shown to be cleared from shellfish tissue less efficiently than bacteria. Therefore, bacteria counts may not always reflect the viral risk of seafood for human consumption (Sharp et al., 2021 ). Regardless, identifying fecal contamination in food samples remains an important safety indicator. In this study, we assessed fecal contamination by performing E. coli counts and also estimated the detection rate of enteric viruses in black shellfish commercialized in local Ecuadorian markets using molecular methods (qRT-PCR). The results reported here demonstrated the circulation of five enteric viruses and highlight the need for permanent surveillance of pathogens in mollusks marketed in our country to determine their quality and safety for human consumption. Materials and Methods Sampling A total of 98 black shellfish ( Anadara tuberculosa and Anadara similis ) samples were collected from markets in different Ecuadorian main land cities (Quito, Cuenca, Esmeraldas, Huaquillas, Guayaquil, Machala) and 3 oysters ( Saccostrea palmula ) samples from their natural environments in the Galapagos archipelago (San Cristobal and Santa Cruz islands under the research permit MAE-DBI-CM-2026-0612) during the year 2021 (from July to December) (Figure 1). For the main land collections, convenience sampling was performed during the rainy and dry seasons, and collection time points occurred weekly or every other week. Each sample consisted of ten raw black shellfish comprising two species, A. tuberculosa and A. similis . Bivalve samples were collected directly from market stalls using sterile bags, kept at 4°C, and transported immediately to the Food Microbiology Laboratory at Universidad San Francisco de Quito (USFQ, Quito) for microbiological and molecular analysis. For the Galapagos, wild mangrove oysters ( S. palmula) were sampled. Bivalves were collected at low tide from volcanic rocks at less than 5 m depth in the intertidal zone of mangrove forests. Their size was approximately 6–7 cm and adults were prioritized. Each oyster was opened on site and removed from its shell, as it was attached to the rock. The samples were transported in sterile Ziplog bags placed in a cooler with ice packs. Oysters were stored at -20 °C at the Galapagos Science Center (USFQ, San Cristobal Island, Ecuador) until their transit to the Food Microbiology Laboratory (USFQ, Quito). For those samples that were not immediately transported alive to the laboratory (Galapagos and some main land collections), bivalve shellfish were frozen and processed for molecular analysis only ( E. coli count was omitted). E. coli count (Most Probable Number technique) Only live, not frozen bivalves were analyzed for E. coli count. A total of 19 samples out of 101 were excluded due to freezing. The Most Probable Number technique (MPN) was used to determine fecal contamination of 82 samples according to the five tubes-three dilution method described by The Centre for Environment, Fisheries, and Aquaculture Science-CEFAS (Stockley, 2024). The method for E. coli count was based on β-glucuronidase production as established by ISO 16649-3. Briefly, 10 live black shellfish were washed and scrubbed under tap water to remove soil, mud, or sand. Shells were opened using sterile instruments. The shellfish meat and intervalvular liquid were kept in a sterile container, and 2 g ± 0.2 of digestive tissue were aseptically removed and used for further viral extraction. Twenty-five g of the remaining flesh was used for E. coli enumeration. The meat was placed into a sterile stomacher bag and 100 mL of 0.1% peptone solution were added. The bag was homogenized for 3 minutes at medium speed, then 125 mL of peptone water were added and mixed thoroughly to get a master 10 -1 dilution. A further 10-fold dilution (10 -2 ) was made by adding 1 mL of the master dilution to 9 mL of peptone water. Five tubes containing 10 mL of double strength fluorocult (MERCK) medium were each inoculated with 10 mL of master dilution (equivalent to 1 g of molluscan shellfish tissue per tube). Five tubes containing 10 mL of single strength fluorocult medium were each inoculated with 1 mL of master dilution (equivalent to 0.1 g of molluscan shellfish tissue per tube). An additional set of five tubes of single strength fluorocult medium was inoculated with 1 mL of the 10 -2 dilution (equivalent to 0.01 g of molluscan shellfish tissue per tube). Positive control tubes inoculated with E. coli strain ATCC 25922 and negative control (uninoculated tubes) were also included in the analysis. Tubes were incubated at 37 °C for 24 ±2 hours. After incubation, each tube was examined to detect a color change from yellow to blue or green, indicating coliform presence. Tubes showing color change were analyzed under UV light and fluorescence detection at 366 nm was considered suggestive of E. coli . A positive indole test was used to confirm the presence of E. coli . Negative tubes at 24 h incubation were re-incubated for 24 more hours. Additionally, subcultures onto Chromocult coliform agar (MERCK) plates were performed to confirm positivity from each tube. Dark blue to violet colonies were identified as E. coli , and pink to red colonies as other coliform bacteria. The number of positive tubes for each dilution was registered and results were interpreted according to tables given by CEFAS ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"GFUzL7i0","properties":{"formattedCitation":"(Stockley, 2024)","plainCitation":"(Stockley, 2024)","noteIndex":0},"citationItems":[{"id":137,"uris":["http://zotero.org/users/1982343/items/EC3TVUDR"],"itemData":{"id":137,"type":"report","language":"English","number":"17","page":"26","publisher":"CEFAS","title":"Generic protocol - Enumeration of Escherichia coli in bivalve molluscan shellfish by the most probable number (MPN) technique (based on ISO 16649-3)","URL":"https://www.cefas.co.uk/nrl/information-centre/nrl-laboratory-protocols/enumeration-of-escherichia-coli-in-molluscan-bivalve-shellfish/","author":[{"family":"Stockley","given":"Louise"}],"issued":{"date-parts":[["2024",3]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Stockley, 2024) . Viral Extraction Based on ISO 15216-1 (International Organization for Standardization, 2017), 2 g ± 0.2 of digestive tissue (DT) were used for viral extraction. DT was finely chopped using sterile scalpels to get a paste. The homogenized sample was placed into falcon tubes and 2 mL of proteinase K solution (Invitrogen, 100µg/mL) was added to the tube. Samples were vortexed (30 seconds) and placed in a shaking incubator at 37 °C for 60 min and 300 rpm. A second incubation step was performed at 60°C for 15 min. Samples were then centrifuged at 3 000 g for 5 min and the supernatant was collected and used for RNA extraction. Extraction of viral RNA (on 250 µL aliquot of the supernatant) was performed using ReliaPrep RNA Cell Miniprep System (Promega) according to the manufacturer’s instructions with modifications (we omitted the DNase treatment step to allow posterior detection of HAdV). Extracted DNA/RNA was eluted on 50 µL of free nuclease water and kept at -80°C immediately after extraction for further analysis. Reverse Transcription PCR Aliquots of 5 µl of RNA from each sample were subjected to reverse transcription (RT). Extracted RNA was pipetted into a PCR tube and placed in a Bio-Rad thermocycler at 97°C for 5 min. The PCR tube was placed in an ice bath for 5 minutes, spun for 10 seconds, and returned to the ice bath. A 15 µL mix containing 1X first strand buffer, 5 mM of DTT, 0.375 mM of dNTPs, 30 ng of random primers, 1 U of RNase out, and 5 U of Super Script II was used for the RT reaction. Cycling conditions included 60 min at 42°C, 70 °C for 15 min, and hold at 4 °C. cDNA was used immediately for qPCR, otherwise, it was kept at -20°C until testing. The multiplex qPCR method EVPrtPCR, described elsewhere ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"6AvnW0uu","properties":{"formattedCitation":"(Pang et al., 2014)","plainCitation":"(Pang et al., 2014)","noteIndex":0},"citationItems":[{"id":139,"uris":["http://zotero.org/users/1982343/items/KZYGE2HQ"],"itemData":{"id":139,"type":"article-journal","container-title":"Journal of Medical Virology","DOI":"10.1002/jmv.23851","ISSN":"01466615","issue":"9","journalAbbreviation":"J. Med. Virol.","language":"en","license":"http://doi.wiley.com/10.1002/tdm_license_1.1","page":"1594-1601","source":"DOI.org (Crossref)","title":"Enhanced enteric virus detection in sporadic gastroenteritis using a multi-target real-time PCR panel: A one-year study: Detection of Enteric Viruses in Acute Gastroenteritis","title-short":"Enhanced enteric virus detection in sporadic gastroenteritis using a multi-target real-time PCR panel","volume":"86","author":[{"family":"Pang","given":"Xiaoli L."},{"family":"Preiksaitis","given":"Jutta K."},{"family":"Lee","given":"Bonita E."}],"issued":{"date-parts":[["2014",9]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Pang et al., 2014) , was used to assess the presence or absence of any of six enteric viruses: Norovirus GI (NoV GI), Norovirus GII (NoV GII), Astrovirus (HAstV), Sapovirus (SaV), Adenovirus (HAdV) and/or Rotavirus (RV). The qPCR amplification was performed in a 10 µL volume reaction containing 5 µL of FUMM (TaqMan™ Fast Universal PCR Master Mix -Applied biosystems by Thermo Fisher Scientific) and 3 µl of cDNA. For NoV GI, NoV GII, RV, HAdV, SaV primers and probes, the final concentration was 4.5 µM, and 1.25 µM, respectively. For HAstV primers and probes, the concentration was 2.25 µM and 0.625 µM, respectively. Cycling conditions included initial denaturation for 20 sec at 95 °C, followed by 45 cycles of 3 sec at 95 °C and 30 sec at 60 °C. The reaction was performed using a Bio-Rad CFX96 Touch Real-Time PCR Detection System. Synthetic positive controls (gBlocks gene fragment from Integrated DNA Technologies) and PCR water were used as positive and negative controls, respectively. Samples showing a Cq ≤38 were considered positive. Statistical Analysis The association between each virus identification and dichotomous variables was evaluated using Fisher´s exact test. Associations showing statistical significance in the descriptive analysis were later explored for association measure (odds ratio) to estimate the effect of seasonality (dry or rainy season), and geographical origin source (San Lorenzo, Puerto El Morrro, Galapagos, Jambelí, Muisne, Puerto Bolivar, Puerto Jeli and Puerto Hualtaco). Because most of the samples were from San Lorenzo while the rest of the localities each had a small number of samples, we categorized the samples as from “San Lorenzo” or as “regions other than San Lorenzo”. Odds ratios were calculated using a logistic regression model. An association was considered statistically significant if the p -value was equal to or lower than 0.05. Statistical analyses were performed using the software SPSS 28.0.1 (IBM), and Excel. Results E. coli count All samples analyzed were positive to E. coli , but seventy samples of black shellfish (85.4 %) showed E. coli counts above the permissible limit (≤ 230 MPN) established by the Ecuadorian regulation INEN 2729 (INEN, 2013) as shown in Table 1. Enteric viral detection We detected at least one enteric virus in 69.3% of the samples. We found one, two, three, and four viruses in 39 (38.6%), 20 (19.8%), 9 (8.9%), and 2 (1.98%) samples, respectively (Table 2). HAdV + RV was the most common combination detected (7 samples, 6.93%). We observed an association between the dry season and HAdV detection, ( p =0.001, Fisher Exact Test) (Table 3). Samples collected during the rainy season were 75% less likely to be positive for HAdV than those collected during the dry season (OR:0.25, 95% CI [0.11, 0.58]). Results of detected viruses by sample origin, showed that samples collected from regions other than San Lorenzo were 4.7 times more likely of testing positive for NoV GI than samples collected from San Lorenzo (95% CI [1.34, 16.7]). Conversely, samples collected from regions other than San Lorenzo were 90% less likely to get impermissible E. coli counts than samples collected from San Lorenzo (OR:0.1, 95% CI [0.02, 0.38]). No significant association was identified between fecal contamination ( E. coli counts) and molecular detection of each enteric virus (p >0.05, Fisher Exact Test) (Table 4). Table 1. Frequency of detection of enteric viruses and E. coli in shellfish by geographical origin ORIGIN Sample N° (%) NoV GI Positive (%) NoV GII Positive (%) RV Positive (%) HAdV Positive (%) HAstV Positive (%) SaV Positive (%) Samples with E. coli counts >230 MPN (%) San Lorenzo 86 (85) 15 (14.85) 4 (3.96) 15 (14.85) 42 (41.58) 10 (10) 10 (10) 64 (78.05) Puerto El Morro 2 (2) 2 (1.98) 1 (0.99) 1 (0.99) 1 (1.22) San Cristóbal 2 (2) 1 (0.99) 1 (1.22) Santa Cruz 1 (1) Jambelí 1 (1) 1(0.99) Muisne 3 (3) 1 (0.99) 1 (0.99) 1 (0.99) 3 (2.97) 2 (2.44) Puerto Bolívar 2 (2) 1 (0.99) 1 (0.99) 1 (0.99) 1 (1.22) Puerto Jeli 1 (1) 1 (0.99) 1 (1.22) San Vicente 2 (2) 1 (0.99) Puerto Hualtaco 1 (1) 1 (0.99) TOTAL 101/101 (100) 21/101 (20.8) 7/101 (6.9) 16/101 (15.8) 50/101 (49.5) 10/101 (10) 10/101 (10) 70/82 (85.4) Table 2. Co-detection of enteric viruses in 101 shellfish samples Two pathogens Three pathogens Four pathogens Combination Positive (%) Combination Positive (%) Combination Positive (%) NoV GI+NoVGII 4 (3.96) RV +HAdV+HAstV 2 (1.98) NoV GI+NoV GII+HAdV +HAstV 1 (0.99) NoV GI+HAdV 2 (1.98) HAdV+HAstV +SaV 1 (0.99) NoV GI+HAdV +HAstV+ SaV 1 (0.99) NoV GI + HAstV 1 (0.99) NoV GI, NoVGII, HAdV 1 (0.99) RV +HAdV 7 (6.93) NoV GII, RV +HAdV 1 (0.99) SaV +HAdV 1 (0.99) NoV GI, HAdV + SaV 2 (1.98) SaV +HAstV 1 (0.99) NoV GI, RV +HAdV 1 (0.99) SaV +RV 2 (1.98) RV+HAstV+SaV 1 (0.99) HAdV +HAstV 2 (1.98) Total 101 (100) Total 101 (100) Total 101 (100) Table 3. Association between seasonality and samples´ origin with viral identification or E. coli count Virus NoV GI NoV GII RV HAdV HAstV SaV Samples with E. coli counts >230 MPN (%) n (%) n (%) n (%) n (%) n (%) n (%) n (%) SEASON Dry 8 (16.3 %) 5 (10.2 %) 9 (18.4 %) 33 (67.4 %) 6 (12.5 %) 3 (6.3 %) 28 (34.1 %) Rainy 13 (27.7 %) 2 (4.3 %) 6 (12.8 %) 16 (34.1 %) * 3 (6.4 %) 6 (12.8 %) 42 (51.2 %) p -value 0.22 0.43 0.58 0.001* 0.49 0.32 0.34 ORIGIN San Lorenzo 15 (17.4 %) 4 (4.7 %) 15 (17.4 %) 42 (42.8 %) 10 (11.8 %) 10 (11.8 %) 64 (91.4 %) Galápagos 0 0 0 1 (33.3 %) 0 0 NA Other 6 (50 %) 3 (25 %) 1 (8.3 %) 7 (58.3 %) 0 0 6 (50 %) * p -value 0.035 * 0.07 0.81 0.74 0.53 0.53 0.002* * statistically significant by Fisher’s exact test and an alpha value of 0.05. Table 4. Association between E. coli count and detected viruses Limit NoV GI n (%) NoV GII n (%) RV n (%) HAdV n (%) HAstV n (%) SaV N (%) Permissible 5 (41.7 %) 2 (16.7 %) 0 5 (41.7 %) 0 0 Non-permissible 14 (20 %) 4 (5.7 %) 11 (15.7 %) 34 (48.6 %) 7 (10.1 %) 8 (11.6 %) Fisher´s exact test showed no association between non-permissible E. coli count and positivity for any virus p >0.05. Discussion In this study, we assessed the presence of five viral human pathogens and one fecal indicator bacteria in bivalves (mainly black shellfish) collected in Ecuadorian main land seafood markets and in their natural environments in the Galapagos archipelago. Black shellfish constitutes an important food resource in Ecuadorian gastronomy, and it is frequently consumed raw (Orden-Mejía et al., 2021 ). Also, wild bivalves are good biological indicators of pathogen contamination of water due to their particle-accumulation feeding style (Fiorito et al., 2021 ; Mosquera et al., 2024 ). While no specific information is available from the Galapagos Islands, studies in other regions have shown that oysters and other bivalves can be contaminated with enteric viruses (Le Guyader et al., 2012 ; Lees, 2000 ), highlighting the need for proper sanitation, wastewater management, and monitoring of bivalve harvesting areas. We detected at least one of five viruses (NoV GI, NoV GII, HAdV, RV, SaV, and HAstV) in 69.3% of 101 samples collected in the second semester of 2021. Importantly, all samples analyzed presented E. coli , and most of the them (85,4%) had high E. coli counts that did not meet the national microbiological criteria set by INEN 2729 (INEN, 2013 ). Samples from shellfish ceviche from Guayaquil have been analyzed for E. coli before and the results indicated ranges from < 10 to 2.5x10 3 CFU/g (Orden-Mejía et al., 2021 ; Yang et al., 2022 ). High E. coli counts (4x10 3 to 2x10 7 CFU/g) in black shellfish have been previously described in Puerto El Morro, and the implementation of purification treatment before commercialization of this bivalve shellfish has been suggested (Delgado, 2018 ). Fecal contamination of oysters, mussels, clams, and other bivalves has been documented at varying frequencies around the world. In India, E. coli has been reported in 100% of samples tested (Das et al., 2020 ). In South America, this indicator of fecal contamination has been described in 51% of shellfish samples analyzed in Brazil (Miotto et al., 2019 ); these data are consistent with our findings; but contrast with the 11.1% found in Argentina (Cammarata et al., 2021 ). E. coli as an indicator of fecal contamination allows predicting the presence of other enteric pathogens such as viruses or parasites in food (Ekici & Dümen, 2019 ), and determines its safety for human consumption. Despite the high levels of fecal contamination found, we did not observe a correlation between the presence of E. coli and the presence of any of the viruses analyzed. This is consistent with the study by Sharp and colleagues who found that E. coli is not a good indicator of viral contamination of shellfish or water since viruses persist in shellfish tissue longer than bacteria, even when purification measures are applied (Sharp et al., 2021 ). This difference in clearance rate between bacteria and viruses may explain the association found between non-permissible E. coli counts in samples collected from San Lorenzo, despite their lower NoV GI positive rate. Among the viruses analyzed, HAdV was more frequently detected (49.5% of the samples). Detection of HAdV has been reported in different classes of shellfish and different rates: 6.3%-11.7% in Taiwan (Nagarajan et al., 2022 ); 21.27% in India (Ghosh et al., 2019 ); 43.3% in Spain (Rodriguez-Manzano et al., 2014 ), and 24.7%-75% in Brazil (Do Nascimento et al., 2022 ; Keller et al., 2019 ). Not many studies have been conducted on food in Latin America. In Brazil, (Keller et al., 2019 ) a high frequency of detection of HAdV was reported in mollusks from mangroves (75%), with higher frequencies in mussels. Both Ghosh (Ghosh et al., 2019 ) and Keller (Keller et al., 2019 ) reported a species-dependent frequency; a higher positivity was attributed to clams or mussels compared to oysters or shrimps. This suggests that shellfish may concentrate or retain viruses differently depending on the species, as proposed for NoV (Le Guyader et al., 2012 ). The most common non-bacterial agents described in gastroenteritis globally are NoV GI and NoV GII (WHO, 2015). They were detected in 20.8% and 6.9% of our samples, respectively. NoV GII (GII.4) leads the worldwide list of noroviruses responsible for human gastroenteritis outbreaks (Hardstaff et al., 2018 ). In Ecuador, NoV GII was described as the most frequent genogroup found in stool samples from children in 2015 (Gastañaduy et al., 2015 ; Lopman et al., 2015 ). Globally, this genogroup was found as the most prevalent in shellfish between 2000 and 2021 (Li et al., 2023 ). In contrast, we found a higher prevalence of NoV GI in black shellfish. Our findings agree with studies reporting an in vitro ability of mollusks to concentrate NoV GI over NoV GII due to specific carbohydrates (including blood group antigens) in shellfish tissue acting as ligands, promoting viral strain-specific accumulation (Le Guyader et al., 2008 , 2012 ; Maalouf et al., 2011 ). Furthermore, NoV GI has been widely associated with shellfish-related outbreaks (Keller et al., 2019 ; Kittigul et al., 2016 ; Moon et al., 2011 ), due to the ability of shellfish to bioaccumulate the virus even when it is present at low levels in the surrounding environment (Yang et al., 2022 ). Most viral testing in shellfish focuses on detecting NoV or HAV, but other viruses including RV are also found in these samples. Kittigul reported up to 8% shellfish contamination with RV using nested PCR in Thailand (Kittigul et al., 2016 ), which is lower than the rate we observed (15.8%). However, the shellfish species analyzed in Thailand’s study were different (cockles, oysters, and mussels); and detection frequencies varied among them, again suggesting that the accumulation may be species-dependent. Panamá reported a higher rate of RV (60%) in A. tuberculosa analyzed through ELISA technique (Bourdett-Stanziola et al., 2022 ). However, the high positivity rate was attributed to the sampling area, which was characterized by high tourist activity and subsequent human wastewater in the mangrove. HAstV and SaV have also been associated with foodborne outbreaks, although in a lesser extent (Diez Valcarce et al., 2021 ; Razizadeh et al., 2022 ). We found each, SaV and HAstV, in 10% of tested samples, which is in line with the results reported in Europe, where virus surveillance in food and shellfish is well developed. In Galicia, Spain, SaV was detected more frequently in seafood, ranging from 17.9% to 37.5% (Varela, Hooper, et al., 2016 ; Varela, Polo, et al., 2016), which is similar to reports from Italy (18.8%) (Fusco et al., 2019 ). As for HAstV, up to 20.8% of samples (mussels and clams) in Italy showed contamination with this agent (Fusco et al., 2019 ). The presence of multiple viruses in shellfish is not uncommon (Le Guyader et al., 2008 ). We describe the coexistence of NoV GI and NoV GII in 3.9% of the samples analyzed. We also identified up to four viruses in the same sample, suggesting that the coexistence of different species, genotypes, and genogroups is common in our country, as described in oyster samples in Brazil (Do Nascimento et al., 2022 ). Despite the reports describing NoV disease peaks in the rainy or winter season (Ludwig-Begall et al., 2021 ), we did not identify any seasonality for NoV GI, NoV GII, RV, SaV, or HAstV. Although Ecuador does not have well-defined seasons, dry and rainy periods are usually demarked during the year. We did not identify associations between these seasons and most of the viruses detected. This may be attributed to the short sampling period considered in our study; longer sampling periods will be required in future studies to better characterize the seasonality of enteric viruses in our country. In contrast to previous reports (Tao et al., 2016 ), we found an association between HAdV and dry season. While a lack of HAdV seasonality was reported in shellfish in Brazil (Do Nascimento et al., 2022 ), a seasonality has been described based on stool sample analysis in the Northern region of this country with a higher prevalence of HAdV during summer and spring (Do Nascimento et al., 2022 ), similar to our findings. The concentration of human enteric pathogens (viruses and bacteria) in bivalves is generally the result of contamination of the environment in which they live, and this may be caused by wastewater (Hassard et al., 2017 ). Mangroves represent a special ecosystem and pollution assessment studies have documented fecal contamination in Ecuadorian mangroves (Pernía et al., 2019 ) and rivers (Vinueza et al., 2021 ). In Quito, the capital of Ecuador, 171 million m 3 of wastewater is produced per year and less than 7% is treated. Not only the wastewater from Quito but from all of Ecuador is collected by several rivers before reaching the Pacific Ocean (Guerrero-Latorre et al., 2018 ). The results obtained in our study underscore these previous reports, although we did not analyze mangrove water or shellfishes collected directly for mangroves to fully support this assumption. Still, efforts to ensure mangrove water quality should be reinforced in our country. Black shellfish are commonly consumed raw in typical Ecuadorian dishes such as ceviche, posing a risk to the consumer, as described elsewhere (Orden-Mejía et al., 2021 ). Post-harvest purification methods, including placing shellfish in clean tanks with purified water before commercialization, are commonly used to remove pathogens or reduce their concentration in shellfish (Yang et al., 2022 ). However, this process is not as effective at removing viruses as it is at removing bacteria (Sharp et al., 2021 ). Proper cooking of seafood (90 degrees Celsius over 90 seconds) is a better strategy to reduce the risks, since high temperatures are effective at inactivating viruses (Bozkurt et al., 2015 ). To the best of our knowledge, this study is the first to identify viral genetic material from black shellfish sold in local markets in Ecuadorian cities. Our findings highlight the need to strengthen assessment tools for the timely identification of viral pathogens in commercial shellfish for risk assessment of food-transmitted diseases. In the future, larger sampling, and including additional sampling areas, as well as genotyping analyses will be needed to better characterize the prevalence and genetic diversity of human pathogens among black shellfish. Conclusions During 2021, five enteric viruses (NoVGI and GII, HAdV, HAstV, SaV and RV) were detected from bivalves collected from sea food markets on the Ecuadorian main land, while only HAdV was identified among oysters from natural environment in the Galapagos Islands. Furthermore, most of these bivalves did not meet national or international food safety criteria regarding E. coli enumeration. These results demonstrate the circulation of viral pathogens within bivalves, water and the Ecuadorian population, highlighting the need to implement surveillance programs to adequately monitor these potential public health risks. Declarations Author Contributions: Conceptualization: Lorena Mejía; Methodology: Mery Ulloa Gonzalez, Eloisa Hasing, Juan Daniel Mosquera, Lorena Mejía; Formal analysis and investigation: Mery Ulloa Gonzalez, Lorena Mejía; Writing - original draft preparation: Mery Ulloa Gonzalez, Pablo Endara, Lorena Mejía; Writing - review and editing: Mery Ulloa Gonzalez, Eloisa Hasing, Juan Daniel Mosquera, Sonia Zapata, Lorena Mejía; Funding acquisition: Lorena Mejía. Funding: This study was funded by USFQ Collaboration Grants 2019 and the USFQ COCIBA Grant 2022. Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. References Bosch, A., Gkogka, E., Le Guyader, F. S., Loisy-Hamon, F., Lee, A., Van Lieshout, L., Marthi, B., Myrmel, M., Sansom, A., Schultz, A. C., Winkler, A., Zuber, S., & Phister, T. 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Hasing","email":"","orcid":"","institution":"University of Alberta","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"E.","lastName":"Hasing","suffix":""},{"id":620275042,"identity":"afcd289e-a1d3-4896-84f3-2e5095f761b3","order_by":2,"name":"Pablo Endara","email":"","orcid":"","institution":"Universidad San Francisco de Quito USFQ","correspondingAuthor":false,"prefix":"","firstName":"Pablo","middleName":"","lastName":"Endara","suffix":""},{"id":620275043,"identity":"fe458536-3a7c-4b71-8b08-6e365225aa35","order_by":3,"name":"Juan Daniel Mosquera","email":"","orcid":"","institution":"Universidad San Francisco de Quito USFQ","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"Daniel","lastName":"Mosquera","suffix":""},{"id":620275044,"identity":"e061c695-2d3f-4494-a99d-1edcd7a210c7","order_by":4,"name":"Sonia Zapata-Mena","email":"","orcid":"","institution":"Universidad San Francisco de Quito USFQ","correspondingAuthor":false,"prefix":"","firstName":"Sonia","middleName":"","lastName":"Zapata-Mena","suffix":""},{"id":620275045,"identity":"5778fb97-842d-4ef3-9e48-0a630026ed64","order_by":5,"name":"Lorena Mejía","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYJACgwQGGwYG5gNAJhvxWtKAqhNI0AIEh0nQojvt8IGCBzXnE+e3MW9g+FB2mIGf/QB+LWa30xIMEo7dTtxwjK2Acca5wwySPQmEtOQYGCSwAbXI9xgw87YdZjC4QcBhZrfzPxgk/DsHdBiPAfNfoBZ7wlpyGAwS2w4kNhwDamEE2SJBUEuagUFiX7IxyC8He86l80icIeiX5GeGP77ZyQJDbOODH2XWcvztBwhYA4wLAyjDAKSWh6B6IGB+ANNCjOpRMApGwSgYgQAAKL1F8u3ILPAAAAAASUVORK5CYII=","orcid":"","institution":"Universidad San Francisco de Quito USFQ","correspondingAuthor":true,"prefix":"","firstName":"Lorena","middleName":"","lastName":"Mejía","suffix":""}],"badges":[],"createdAt":"2026-04-01 21:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9296080/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9296080/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106627778,"identity":"a87854b8-e196-4ea4-85e3-37ac7e52fa3f","added_by":"auto","created_at":"2026-04-10 15:12:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":241225,"visible":true,"origin":"","legend":"\u003cp\u003eSampling sites for 101 bivalves samples from main land and Galapagos islands in Ecuador\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9296080/v1/e672e085cba270adcd985932.png"},{"id":107968289,"identity":"d3b2148d-7492-4128-ab51-feb62b547d8f","added_by":"auto","created_at":"2026-04-28 06:11:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":639990,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9296080/v1/efa3fed1-a1af-42d6-94b2-21f39927bacc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Surveillance of enteric viruses in bivalves from Ecuador during the year 2021","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the latest global estimates, there are at least 600\u0026nbsp;million cases of foodborne diseases (FBDs) annually resulting in 420,000 deaths (WHO, 2015), with Norovirus (NoV) being the leading agent of foodborne disease cases also accounting for a high mortality burden (35 000 foodborne associated deaths globally) (Goyal \u0026amp; Cannon, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition to NoV, human Adenovirus (HAdV), Astrovirus (HAstV), Sapovirus (SaV), and Rotavirus (RV) have also been described as agents of food and waterborne diseases (Goyal \u0026amp; Cannon, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Except for HAdV, the other four enteric viruses are included in the list of 31 major foodborne pathogens identified by the CDC (Scallan et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Contamination of water and food, which contributes to the fecal-oral transmission of enteric viruses, is facilitated by the low number of viral particles capable of causing human infection (18 for NoV), the high number of viruses shed in feces (up to 10\u003csup\u003e10\u003c/sup\u003e per gram), and the viral stability in the environment (Goyal \u0026amp; Cannon, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Viral contamination of food can occur at two different stages of food production: preharvest or postharvest. Preharvest contamination results from environmental contamination associated with wastewater and it is common for seafood and vegetables. Postharvest contamination is common for ready-to-eat foods, and it is associated with bad hygiene practices (Bosch et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBivalve shellfish have been widely described as reservoirs and vectors of human pathogens and are responsible for more than 60% of foodborne outbreaks worldwide (Butt, Aldridge, \u0026amp; Sander, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Butt, Aldridge, \u0026amp; Sanders, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This fact can be attributed to their feeding mechanism through filtration which allows them to concentrate pathogens from the surrounding water (Yang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A long list of microorganisms such as viruses (including human calicivirus NoV and HAstV, and hepatitis A virus, hepatitis E virus, RV, HAdV, enterovirus) (Lees, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2000\u003c/span\u003e); bacteria (\u003cem\u003eVibrio\u003c/em\u003e spp., \u003cem\u003eSalmonella\u003c/em\u003e spp., \u003cem\u003eE. coli\u003c/em\u003e Shigellae, \u003cem\u003eAeromonas\u003c/em\u003e spp., \u003cem\u003ePlesiomonas\u003c/em\u003e spp.) and parasites (both protozoa and helminths), are transmitted to humans by ingesting contaminated raw shellfish (Butt, Aldridge, \u0026amp; Sander, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Butt, Aldridge, \u0026amp; Sanders, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2004\u003c/span\u003e); which can be an important issue in Ecuador because raw or undercooked shellfish is consumed frequently (Orden-Mej\u0026iacute;a et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eViral FBDs are at the top of the food safety priorities established in the EU (Rowe \u0026amp; Bolger, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In addition, the development of policies and programs to strengthen food safety is encouraged by the WHO (WHO, 2015), and assessment and control of foodborne pathogens is one of the key issues (Bosch et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Ecuador surveillance focuses on limited pathogens considering only \u003cem\u003eSalmonella\u003c/em\u003e spp., \u003cem\u003eE. coli\u003c/em\u003e Shigellae, and hepatitis A virus (HAV) for mandatory reporting, even though these agents represent only a quarter of the FBD cases identified (MSP, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). During 2024, 13 959 cases of FBDs were documented; and 10 799 were categorized as \u0026ldquo;other food poisoning\u0026rdquo; without specifying the etiological agent (MSP, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This illustrates the limited characterizing of FBD agents in Ecuador, where only a few studies have described viruses in food, including the detection of noroviruses and HAV in strawberries and spinach (Salazar et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This highlights the need to strengthen surveillance and tools to identify the specific pathogens circulating in our country responsible for this important burden, allowing us to better characterize the local epidemiology.\u003c/p\u003e \u003cp\u003eOn the other hand, \u003cem\u003eE. coli\u003c/em\u003e count has been widely used as a marker for fecal contamination of food assessing their safety for human consumption (Devane et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), however, viruses have been shown to be cleared from shellfish tissue less efficiently than bacteria. Therefore, bacteria counts may not always reflect the viral risk of seafood for human consumption (Sharp et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Regardless, identifying fecal contamination in food samples remains an important safety indicator.\u003c/p\u003e \u003cp\u003eIn this study, we assessed fecal contamination by performing \u003cem\u003eE. coli\u003c/em\u003e counts and also estimated the detection rate of enteric viruses in black shellfish commercialized in local Ecuadorian markets using molecular methods (qRT-PCR). The results reported here demonstrated the circulation of five enteric viruses and highlight the need for permanent surveillance of pathogens in mollusks marketed in our country to determine their quality and safety for human consumption.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003ch3\u003eSampling\u003c/h3\u003e\n\u003cp\u003eA total of 98 black shellfish (\u003cem\u003eAnadara tuberculosa\u003c/em\u003e and \u003cem\u003eAnadara similis\u003c/em\u003e) samples were collected from markets in different Ecuadorian main land cities (Quito, Cuenca, Esmeraldas, Huaquillas, Guayaquil, Machala) and 3 oysters (\u003cem\u003eSaccostrea palmula\u003c/em\u003e) samples from their natural environments in the Galapagos archipelago (San Cristobal and Santa Cruz islands under the research permit MAE-DBI-CM-2026-0612) during the year 2021 (from July to December) (Figure 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the main land collections, convenience sampling was performed during the rainy and dry seasons, and collection time points occurred weekly or every other week. Each sample consisted of ten raw black shellfish comprising two species, \u003cem\u003eA. tuberculosa\u003c/em\u003e and \u003cem\u003eA. similis\u003c/em\u003e. Bivalve samples were collected directly from market stalls using sterile bags, kept at 4\u0026deg;C, and transported immediately to the Food Microbiology Laboratory at Universidad San Francisco de Quito (USFQ, Quito) for microbiological and molecular analysis. For the Galapagos, wild mangrove oysters (\u003cem\u003eS. palmula)\u0026nbsp;\u003c/em\u003ewere sampled.\u0026nbsp;Bivalves were collected at low tide from volcanic rocks at less than 5 m depth in the intertidal zone of mangrove forests. Their size was approximately 6\u0026ndash;7 cm and adults were prioritized. Each oyster was opened on site and removed from its shell, as it was attached to the rock. The samples were transported in sterile Ziplog bags placed in a cooler with ice packs. Oysters were stored at -20 \u0026deg;C at the Galapagos Science Center (USFQ, San Cristobal Island, Ecuador) until their transit to the Food Microbiology Laboratory (USFQ, Quito). For those samples that were not immediately transported alive to the laboratory (Galapagos and some main land collections), bivalve shellfish were frozen and processed for molecular analysis only (\u003cem\u003eE. coli\u003c/em\u003e count was omitted).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eE. coli\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ecount (Most Probable Number technique)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOnly live, not frozen bivalves were analyzed for \u003cem\u003eE. coli\u003c/em\u003e count. A total of 19 samples out of 101 were excluded due to freezing. The Most Probable Number technique (MPN) was used to determine fecal contamination of 82 samples according to the five tubes-three dilution method described by The Centre for Environment, Fisheries, and Aquaculture Science-CEFAS (Stockley, 2024). The method for \u003cem\u003eE. coli\u0026nbsp;\u003c/em\u003ecount was based on \u0026beta;-glucuronidase production as established by ISO 16649-3.\u003c/p\u003e\n\u003cp\u003eBriefly, 10 live black shellfish were washed and scrubbed under tap water to remove soil, mud, or sand. Shells were opened using sterile instruments. The shellfish meat and intervalvular liquid were kept in a sterile container, and 2 g \u0026plusmn; 0.2 of digestive tissue were aseptically removed and used for further viral extraction.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTwenty-five g of the remaining flesh was used for \u003cem\u003eE. coli\u003c/em\u003e enumeration. The meat was placed into a sterile stomacher bag and 100 mL of 0.1% peptone solution were added. The bag was homogenized for 3 minutes at medium speed, then 125 mL of peptone water were added and mixed thoroughly to get a master 10\u003csup\u003e-1\u003c/sup\u003e dilution.\u003c/p\u003e\n\u003cp\u003eA further 10-fold dilution (10\u003csup\u003e-2\u003c/sup\u003e) was made by adding 1 mL of the master dilution to 9 mL of peptone water. Five tubes containing 10 mL of double strength fluorocult (MERCK) medium were each inoculated with 10 mL of master dilution (equivalent to 1 g of molluscan shellfish tissue per tube). Five tubes containing 10 mL of single strength fluorocult medium were each inoculated with 1 mL of master dilution (equivalent to 0.1 g of molluscan shellfish tissue per tube). An additional set of five tubes of single strength fluorocult medium was inoculated with 1 mL of the 10\u003csup\u003e-2\u003c/sup\u003e dilution (equivalent to 0.01 g of molluscan shellfish tissue per tube). Positive control tubes inoculated with \u003cem\u003eE. coli\u003c/em\u003e strain ATCC 25922 and negative control (uninoculated tubes) were also included in the analysis. Tubes were incubated at 37 \u0026deg;C for 24 \u0026plusmn;2 hours. After incubation, each tube was examined to detect a color change from yellow to blue or green, indicating coliform presence. Tubes showing color change were analyzed under UV light and fluorescence detection at 366 nm was considered suggestive of \u003cem\u003eE. coli\u003c/em\u003e. A positive indole test was used to confirm the presence of \u003cem\u003eE. coli\u003c/em\u003e. Negative tubes at 24 h incubation were re-incubated for 24 more hours.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, subcultures onto Chromocult coliform agar (MERCK) plates were performed to confirm positivity from each tube. Dark blue to violet colonies were identified as \u003cem\u003eE. coli\u003c/em\u003e, and pink to red colonies as other coliform bacteria. The number of positive tubes for each dilution was registered and results were interpreted according to tables given by CEFAS \u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-begin'\u003e\u003c/span\u003e\u0026nbsp;ADDIN ZOTERO_ITEM CSL_CITATION {\u0026quot;citationID\u0026quot;:\u0026quot;GFUzL7i0\u0026quot;,\u0026quot;properties\u0026quot;:{\u0026quot;formattedCitation\u0026quot;:\u0026quot;(Stockley, 2024)\u0026quot;,\u0026quot;plainCitation\u0026quot;:\u0026quot;(Stockley, 2024)\u0026quot;,\u0026quot;noteIndex\u0026quot;:0},\u0026quot;citationItems\u0026quot;:[{\u0026quot;id\u0026quot;:137,\u0026quot;uris\u0026quot;:[\u0026quot;http://zotero.org/users/1982343/items/EC3TVUDR\u0026quot;],\u0026quot;itemData\u0026quot;:{\u0026quot;id\u0026quot;:137,\u0026quot;type\u0026quot;:\u0026quot;report\u0026quot;,\u0026quot;language\u0026quot;:\u0026quot;English\u0026quot;,\u0026quot;number\u0026quot;:\u0026quot;17\u0026quot;,\u0026quot;page\u0026quot;:\u0026quot;26\u0026quot;,\u0026quot;publisher\u0026quot;:\u0026quot;CEFAS\u0026quot;,\u0026quot;title\u0026quot;:\u0026quot;Generic protocol - Enumeration of Escherichia coli in bivalve molluscan shellfish by the most probable number (MPN) technique (based on ISO 16649-3)\u0026quot;,\u0026quot;URL\u0026quot;:\u0026quot;https://www.cefas.co.uk/nrl/information-centre/nrl-laboratory-protocols/enumeration-of-escherichia-coli-in-molluscan-bivalve-shellfish/\u0026quot;,\u0026quot;author\u0026quot;:[{\u0026quot;family\u0026quot;:\u0026quot;Stockley\u0026quot;,\u0026quot;given\u0026quot;:\u0026quot;Louise\u0026quot;}],\u0026quot;issued\u0026quot;:{\u0026quot;date-parts\u0026quot;:[[\u0026quot;2024\u0026quot;,3]]}}}],\u0026quot;schema\u0026quot;:\u0026quot;https://github.com/citation-style-language/schema/raw/master/csl-citation.json\u0026quot;} \u003cspan style='mso-element:field-separator'\u003e\u003c/span\u003e\u003c![endif]--\u003e(Stockley, 2024)\u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-end'\u003e\u003c/span\u003e\u003c![endif]--\u003e.\u003c/p\u003e\n\u003ch3\u003eViral Extraction\u003c/h3\u003e\n\u003cp\u003eBased on ISO 15216-1\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(International Organization for Standardization, 2017), 2 g \u0026plusmn; 0.2 of digestive tissue (DT) were used for viral extraction. DT was finely chopped using sterile scalpels to get a paste. The homogenized sample was placed into falcon tubes and 2 mL of proteinase K solution (Invitrogen, 100\u0026micro;g/mL) was added to the tube. Samples were vortexed (30 seconds) and placed in a shaking incubator at 37 \u0026deg;C for 60 min and 300 rpm. A second incubation step was performed at 60\u0026deg;C for 15 min. Samples were then centrifuged at 3 000 g for 5 min and the supernatant was collected and used for RNA extraction. Extraction of viral RNA (on 250 \u0026micro;L aliquot of the supernatant) was performed using ReliaPrep RNA Cell Miniprep System (Promega) according to the manufacturer\u0026rsquo;s instructions with modifications (we omitted the DNase treatment step to allow posterior detection of HAdV). Extracted DNA/RNA was eluted on 50 \u0026micro;L of free nuclease water and kept at -80\u0026deg;C immediately after extraction for further analysis.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eReverse Transcription PCR\u003c/h3\u003e\n\u003cp\u003eAliquots of 5 \u0026micro;l of RNA from each sample were subjected to reverse transcription (RT). Extracted RNA was pipetted into a PCR tube and placed in a Bio-Rad thermocycler at 97\u0026deg;C for 5 min. The PCR tube was placed in an ice bath for 5 minutes, spun for 10 seconds, and returned to the ice bath. A 15 \u0026micro;L mix containing 1X first strand buffer, 5 mM of DTT, 0.375 mM of dNTPs, 30 ng of random primers, 1 U of RNase out, and 5 U of Super Script II was used for the RT reaction. Cycling conditions included 60 min at 42\u0026deg;C, 70 \u0026deg;C for 15 min, and hold at 4 \u0026deg;C. cDNA was used immediately for qPCR, otherwise, it was kept at -20\u0026deg;C until testing.\u003c/p\u003e\n\u003cp\u003eThe multiplex qPCR method EVPrtPCR, described elsewhere \u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-begin'\u003e\u003c/span\u003e\u0026nbsp;ADDIN ZOTERO_ITEM CSL_CITATION {\u0026quot;citationID\u0026quot;:\u0026quot;6AvnW0uu\u0026quot;,\u0026quot;properties\u0026quot;:{\u0026quot;formattedCitation\u0026quot;:\u0026quot;(Pang et al., 2014)\u0026quot;,\u0026quot;plainCitation\u0026quot;:\u0026quot;(Pang et al., 2014)\u0026quot;,\u0026quot;noteIndex\u0026quot;:0},\u0026quot;citationItems\u0026quot;:[{\u0026quot;id\u0026quot;:139,\u0026quot;uris\u0026quot;:[\u0026quot;http://zotero.org/users/1982343/items/KZYGE2HQ\u0026quot;],\u0026quot;itemData\u0026quot;:{\u0026quot;id\u0026quot;:139,\u0026quot;type\u0026quot;:\u0026quot;article-journal\u0026quot;,\u0026quot;container-title\u0026quot;:\u0026quot;Journal of Medical Virology\u0026quot;,\u0026quot;DOI\u0026quot;:\u0026quot;10.1002/jmv.23851\u0026quot;,\u0026quot;ISSN\u0026quot;:\u0026quot;01466615\u0026quot;,\u0026quot;issue\u0026quot;:\u0026quot;9\u0026quot;,\u0026quot;journalAbbreviation\u0026quot;:\u0026quot;J. Med. Virol.\u0026quot;,\u0026quot;language\u0026quot;:\u0026quot;en\u0026quot;,\u0026quot;license\u0026quot;:\u0026quot;http://doi.wiley.com/10.1002/tdm_license_1.1\u0026quot;,\u0026quot;page\u0026quot;:\u0026quot;1594-1601\u0026quot;,\u0026quot;source\u0026quot;:\u0026quot;DOI.org (Crossref)\u0026quot;,\u0026quot;title\u0026quot;:\u0026quot;Enhanced enteric virus detection in sporadic gastroenteritis using a multi-target real-time PCR panel: A one-year study: Detection of Enteric Viruses in Acute Gastroenteritis\u0026quot;,\u0026quot;title-short\u0026quot;:\u0026quot;Enhanced enteric virus detection in sporadic gastroenteritis using a multi-target real-time PCR panel\u0026quot;,\u0026quot;volume\u0026quot;:\u0026quot;86\u0026quot;,\u0026quot;author\u0026quot;:[{\u0026quot;family\u0026quot;:\u0026quot;Pang\u0026quot;,\u0026quot;given\u0026quot;:\u0026quot;Xiaoli L.\u0026quot;},{\u0026quot;family\u0026quot;:\u0026quot;Preiksaitis\u0026quot;,\u0026quot;given\u0026quot;:\u0026quot;Jutta K.\u0026quot;},{\u0026quot;family\u0026quot;:\u0026quot;Lee\u0026quot;,\u0026quot;given\u0026quot;:\u0026quot;Bonita E.\u0026quot;}],\u0026quot;issued\u0026quot;:{\u0026quot;date-parts\u0026quot;:[[\u0026quot;2014\u0026quot;,9]]}}}],\u0026quot;schema\u0026quot;:\u0026quot;https://github.com/citation-style-language/schema/raw/master/csl-citation.json\u0026quot;} \u003cspan style='mso-element:field-separator'\u003e\u003c/span\u003e\u003c![endif]--\u003e(Pang et al., 2014)\u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-end'\u003e\u003c/span\u003e\u003c![endif]--\u003e, was used to assess the presence or absence of any of six enteric viruses: Norovirus GI (NoV GI), Norovirus GII (NoV GII), Astrovirus (HAstV), Sapovirus (SaV), Adenovirus (HAdV) and/or Rotavirus (RV).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe qPCR amplification was performed in a 10 \u0026micro;L volume reaction containing 5 \u0026micro;L of FUMM (TaqMan\u0026trade; Fast Universal PCR Master Mix -Applied biosystems by Thermo Fisher Scientific) and 3 \u0026micro;l of cDNA. For NoV GI, NoV GII, RV, HAdV, SaV primers and probes, the final concentration was 4.5 \u0026micro;M, and 1.25 \u0026micro;M, respectively. For HAstV primers and probes, the concentration was 2.25 \u0026micro;M and 0.625 \u0026micro;M, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCycling conditions included initial denaturation for 20 sec at 95 \u0026deg;C, followed by 45 cycles of 3 sec at 95 \u0026deg;C and 30 sec at 60 \u0026deg;C. The reaction was performed using a Bio-Rad CFX96 Touch Real-Time PCR Detection System. Synthetic positive controls (gBlocks gene fragment from Integrated DNA Technologies) and PCR water were used as positive and negative controls, respectively. Samples showing a Cq \u0026le;38 were considered positive.\u003c/p\u003e\n\u003ch3\u003eStatistical Analysis\u003c/h3\u003e\n\u003cp\u003eThe association between each virus identification and dichotomous variables was evaluated using Fisher\u0026acute;s exact test. Associations showing statistical significance in the descriptive analysis were later explored for association measure (odds ratio) to estimate the effect of seasonality (dry or rainy season), and geographical origin source (San Lorenzo, Puerto El Morrro, Galapagos, Jambel\u0026iacute;, Muisne, Puerto Bolivar, Puerto Jeli and Puerto Hualtaco). Because most of the samples were from San Lorenzo while the rest of the localities each had a small number of samples, we categorized the samples as from \u0026ldquo;San Lorenzo\u0026rdquo; or as \u0026ldquo;regions other than San Lorenzo\u0026rdquo;. Odds ratios were calculated using a logistic regression model. An association was considered statistically significant if the \u003cem\u003ep\u003c/em\u003e-value was equal to or lower than 0.05. Statistical analyses were performed using the software SPSS 28.0.1 (IBM), and Excel.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e count\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll samples analyzed were positive to \u003cem\u003eE. coli\u003c/em\u003e, but seventy samples of black shellfish (85.4 %) showed \u003cem\u003eE. coli\u003c/em\u003e counts above the permissible limit (\u0026le; 230 MPN) established by the Ecuadorian regulation INEN 2729 (INEN, 2013) as shown in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEnteric viral detection\u003c/p\u003e\n\u003cp\u003eWe detected at least one enteric virus in 69.3% of the samples. We found one, two, three, and four viruses in 39 (38.6%), 20 (19.8%), 9 (8.9%), and 2 (1.98%) samples, respectively (Table 2). HAdV + RV was the most common combination detected (7 samples, 6.93%). We observed an association between the dry season and HAdV detection, (\u003cem\u003ep\u003c/em\u003e=0.001, Fisher Exact Test) (Table 3). Samples collected during the rainy season were 75% less likely to be positive for HAdV than those collected during the dry season (OR:0.25, 95% CI [0.11, 0.58]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults of detected viruses by sample origin, showed that samples collected from regions other than San Lorenzo were 4.7 times more likely of testing positive for NoV GI than samples collected from San Lorenzo (95% CI [1.34, 16.7]). Conversely, samples collected from regions other than San Lorenzo were 90% less likely to get impermissible \u003cem\u003eE. coli\u003c/em\u003e counts than samples collected from San Lorenzo (OR:0.1, 95% CI [0.02, 0.38]). No significant association was identified between fecal contamination (\u003cem\u003eE. coli\u003c/em\u003e counts) and molecular detection of each enteric virus (p \u0026gt;0.05, Fisher Exact Test) (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"875\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" style=\"width: 875px;\"\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFrequency of detection of enteric viruses and \u003cem\u003eE. coli\u003c/em\u003e in shellfish by geographical origin\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003eORIGIN\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003eN\u0026deg; (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\u003cstrong\u003eNoV GI\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003ePositive (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u003cstrong\u003eNoV GII\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003ePositive (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cstrong\u003eRV\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003ePositive (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cstrong\u003eHAdV\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003ePositive (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cstrong\u003eHAstV\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003ePositive (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u003cstrong\u003eSaV \u0026nbsp; \u0026nbsp; Positive (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u003cstrong\u003eSamples with\u003cem\u003e\u0026nbsp;E. coli\u0026nbsp;\u003c/em\u003ecounts\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u0026gt;230 MPN\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003eSan Lorenzo\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e86 (85)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e15 (14.85)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e4 (3.96)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e15 (14.85)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e42 (41.58)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e10 (10)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e10 (10)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e64 (78.05)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003ePuerto El Morro\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e2 (2)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e2 (1.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e1 (1.22)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003eSan Crist\u0026oacute;bal\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e2 (2)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e1 (1.22)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003eSanta Cruz\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e1 (1)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003eJambel\u0026iacute;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e1 (1)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e1(0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003eMuisne\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e3 (3)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e3 (2.97)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e2 (2.44)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003ePuerto Bol\u0026iacute;var\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e2 (2)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e1 (1.22)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003ePuerto Jeli\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e1 (1)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e1 (1.22)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003eSan Vicente\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e2 (2)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003ePuerto Hualtaco\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e1 (1)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u003cstrong\u003eTOTAL\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\u003cstrong\u003e101/101 (100)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\u003cstrong\u003e21/101 (20.8)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u003cstrong\u003e7/101 (6.9)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cstrong\u003e16/101 (15.8)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cstrong\u003e50/101 (49.5)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cstrong\u003e10/101 (10)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u003cstrong\u003e10/101 (10)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u003cstrong\u003e70/82 (85.4)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"864\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 864px;\"\u003e\u003cstrong\u003e\u003cspan id=\"_Toc136970728\"\u003eTable 2. Co-detection of enteric viruses in 101 shellfish samples\u003c/span\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 242px;\"\u003e\u003cstrong\u003eTwo pathogens\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 276px;\"\u003e\u003cstrong\u003eThree pathogens\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 346px;\"\u003e\u003cstrong\u003eFour pathogens\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eCombination\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003ePositive (%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003eCombination\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003ePositive (%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003eCombination\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003ePositive (%)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eNoV GI+NoVGII\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e4 (3.96)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003eRV +HAdV+HAstV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e2 (1.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003eNoV GI+NoV GII+HAdV +HAstV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eNoV GI+HAdV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e2 (1.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003eHAdV+HAstV +SaV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003eNoV GI+HAdV +HAstV+ SaV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eNoV GI + HAstV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003eNoV GI, NoVGII, HAdV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eRV +HAdV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e7 (6.93)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003eNoV GII, RV +HAdV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eSaV +HAdV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003eNoV GI, HAdV + SaV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e2 (1.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eSaV +HAstV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003eNoV GI, RV +HAdV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eSaV +RV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e2 (1.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003eRV+HAstV+SaV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e1 (0.99)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003eHAdV +HAstV\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e2 (1.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 145px;\"\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cstrong\u003e101 (100)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\u003cstrong\u003e101 (100)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\u003cstrong\u003e101 (100)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"913\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 913px;\"\u003e\u003cstrong\u003e\u003cspan id=\"_Toc136970729\"\u003eTable 3. Association between seasonality and samples\u0026acute; origin with viral identification or \u003cem\u003eE. coli\u003c/em\u003e count\u003c/span\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 81px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 118px;\"\u003e\u003cstrong\u003eVirus\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\u003cstrong\u003eNoV GI\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u003cstrong\u003eNoV GII\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cstrong\u003eRV\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u003cstrong\u003eHAdV\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\u003cstrong\u003eHAstV\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cstrong\u003eSaV\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\u003cstrong\u003eSamples with \u003cem\u003eE. coli\u003c/em\u003e counts \u0026gt;230 MPN (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e (%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e (%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e (%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e (%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e (%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e (%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e (%)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 81px;\"\u003eSEASON\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003eDry\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e8 (16.3 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e5 (10.2 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e9 (18.4 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e33 (67.4 %)\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e6 (12.5 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e3 (6.3 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e28 (34.1 %)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 118px;\"\u003eRainy\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e13 (27.7 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e2 (4.3 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e6 (12.8 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u003cstrong\u003e16 (34.1 %) *\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e3 (6.4 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e6 (12.8 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e42 (51.2 %)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 118px;\"\u003e\u003cem\u003ep\u003c/em\u003e-value\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e0.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e0.58\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e0.49\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 81px;\"\u003eORIGIN\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003eSan Lorenzo\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e15 (17.4 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e4 (4.7 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e15 (17.4 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e42 (42.8 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e10 (11.8 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e10 (11.8 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e64 (91.4 %)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 118px;\"\u003eGal\u0026aacute;pagos\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e1 (33.3 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003eNA\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 118px;\"\u003eOther\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e6 (50 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e3 (25 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e1 (8.3 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e7 (58.3 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\u003cstrong\u003e6 (50 %) *\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 118px;\"\u003e\u003cem\u003ep\u003c/em\u003e-value\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\u003cstrong\u003e0.035 *\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e0.81\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e0.74\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e0.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e0.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\u003cstrong\u003e0.002*\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 81px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"8\" style=\"width: 832px;\"\u003e* statistically significant by Fisher\u0026rsquo;s exact test and an alpha value of 0.05.\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 606px;\"\u003e\u003cstrong\u003e\u003cspan id=\"_Toc131328081\"\u003eTable 4. Association between \u003cem\u003eE. coli\u003c/em\u003e count and detected viruses\u003c/span\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003eLimit\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\u003cstrong\u003eNoV GI\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\u003cstrong\u003eNoV GII\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\u003cstrong\u003eRV\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\u003cstrong\u003eHAdV\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cstrong\u003eHAstV\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\u003cstrong\u003eSaV\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003ePermissible\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e5 (41.7 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e2 (16.7 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e5 (41.7 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003eNon-permissible\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e14 (20 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e4 (5.7 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e11 (15.7 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e34 (48.6 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e7 (10.1 %)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e8 (11.6 %)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 606px;\"\u003eFisher\u0026acute;s exact test showed no association between non-permissible \u003cem\u003eE. coli\u003c/em\u003e count and positivity for any virus\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u0026gt;0.05.\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we assessed the presence of five viral human pathogens and one fecal indicator bacteria in bivalves (mainly black shellfish) collected in Ecuadorian main land seafood markets and in their natural environments in the Galapagos archipelago. Black shellfish constitutes an important food resource in Ecuadorian gastronomy, and it is frequently consumed raw (Orden-Mej\u0026iacute;a et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Also, wild bivalves are good biological indicators of pathogen contamination of water due to their particle-accumulation feeding style (Fiorito et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mosquera et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). While no specific information is available from the Galapagos Islands, studies in other regions have shown that oysters and other bivalves can be contaminated with enteric viruses (Le Guyader et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Lees, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), highlighting the need for proper sanitation, wastewater management, and monitoring of bivalve harvesting areas.\u003c/p\u003e \u003cp\u003eWe detected at least one of five viruses (NoV GI, NoV GII, HAdV, RV, SaV, and HAstV) in 69.3% of 101 samples collected in the second semester of 2021. Importantly, all samples analyzed presented \u003cem\u003eE. coli\u003c/em\u003e, and most of the them (85,4%) had high \u003cem\u003eE. coli\u003c/em\u003e counts that did not meet the national microbiological criteria set by INEN 2729 (INEN, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Samples from shellfish ceviche from Guayaquil have been analyzed for \u003cem\u003eE. coli\u003c/em\u003e before and the results indicated ranges from \u0026lt;\u0026thinsp;10 to 2.5x10\u003csup\u003e3\u003c/sup\u003e CFU/g (Orden-Mej\u0026iacute;a et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). High \u003cem\u003eE. coli\u003c/em\u003e counts (4x10\u003csup\u003e3\u003c/sup\u003e to 2x10\u003csup\u003e7\u003c/sup\u003e CFU/g) in black shellfish have been previously described in Puerto El Morro, and the implementation of purification treatment before commercialization of this bivalve shellfish has been suggested (Delgado, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFecal contamination of oysters, mussels, clams, and other bivalves has been documented at varying frequencies around the world. In India, \u003cem\u003eE. coli\u003c/em\u003e has been reported in 100% of samples tested (Das et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In South America, this indicator of fecal contamination has been described in 51% of shellfish samples analyzed in Brazil (Miotto et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); these data are consistent with our findings; but contrast with the 11.1% found in Argentina (Cammarata et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). \u003cem\u003eE. coli\u003c/em\u003e as an indicator of fecal contamination allows predicting the presence of other enteric pathogens such as viruses or parasites in food (Ekici \u0026amp; D\u0026uuml;men, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and determines its safety for human consumption. Despite the high levels of fecal contamination found, we did not observe a correlation between the presence of \u003cem\u003eE. coli\u003c/em\u003e and the presence of any of the viruses analyzed. This is consistent with the study by Sharp and colleagues who found that \u003cem\u003eE. coli\u003c/em\u003e is not a good indicator of viral contamination of shellfish or water since viruses persist in shellfish tissue longer than bacteria, even when purification measures are applied (Sharp et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This difference in clearance rate between bacteria and viruses may explain the association found between non-permissible \u003cem\u003eE. coli\u003c/em\u003e counts in samples collected from San Lorenzo, despite their lower NoV GI positive rate.\u003c/p\u003e \u003cp\u003eAmong the viruses analyzed, HAdV was more frequently detected (49.5% of the samples). Detection of HAdV has been reported in different classes of shellfish and different rates: 6.3%-11.7% in Taiwan (Nagarajan et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); 21.27% in India (Ghosh et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); 43.3% in Spain (Rodriguez-Manzano et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and 24.7%-75% in Brazil (Do Nascimento et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Keller et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Not many studies have been conducted on food in Latin America. In Brazil, (Keller et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) a high frequency of detection of HAdV was reported in mollusks from mangroves (75%), with higher frequencies in mussels. Both Ghosh (Ghosh et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Keller (Keller et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported a species-dependent frequency; a higher positivity was attributed to clams or mussels compared to oysters or shrimps. This suggests that shellfish may concentrate or retain viruses differently depending on the species, as proposed for NoV (Le Guyader et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe most common non-bacterial agents described in gastroenteritis globally are NoV GI and NoV GII (WHO, 2015). They were detected in 20.8% and 6.9% of our samples, respectively. NoV GII (GII.4) leads the worldwide list of noroviruses responsible for human gastroenteritis outbreaks (Hardstaff et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In Ecuador, NoV GII was described as the most frequent genogroup found in stool samples from children in 2015 (Gasta\u0026ntilde;aduy et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lopman et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Globally, this genogroup was found as the most prevalent in shellfish between 2000 and 2021 (Li et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In contrast, we found a higher prevalence of NoV GI in black shellfish. Our findings agree with studies reporting an \u003cem\u003ein vitro\u003c/em\u003e ability of mollusks to concentrate NoV GI over NoV GII due to specific carbohydrates (including blood group antigens) in shellfish tissue acting as ligands, promoting viral strain-specific accumulation (Le Guyader et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Maalouf et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Furthermore, NoV GI has been widely associated with shellfish-related outbreaks (Keller et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kittigul et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Moon et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), due to the ability of shellfish to bioaccumulate the virus even when it is present at low levels in the surrounding environment (Yang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost viral testing in shellfish focuses on detecting NoV or HAV, but other viruses including RV are also found in these samples. Kittigul reported up to 8% shellfish contamination with RV using nested PCR in Thailand (Kittigul et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which is lower than the rate we observed (15.8%). However, the shellfish species analyzed in Thailand\u0026rsquo;s study were different (cockles, oysters, and mussels); and detection frequencies varied among them, again suggesting that the accumulation may be species-dependent. Panam\u0026aacute; reported a higher rate of RV (60%) in \u003cem\u003eA. tuberculosa\u003c/em\u003e analyzed through ELISA technique (Bourdett-Stanziola et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the high positivity rate was attributed to the sampling area, which was characterized by high tourist activity and subsequent human wastewater in the mangrove.\u003c/p\u003e \u003cp\u003eHAstV and SaV have also been associated with foodborne outbreaks, although in a lesser extent (Diez Valcarce et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Razizadeh et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We found each, SaV and HAstV, in 10% of tested samples, which is in line with the results reported in Europe, where virus surveillance in food and shellfish is well developed. In Galicia, Spain, SaV was detected more frequently in seafood, ranging from 17.9% to 37.5% (Varela, Hooper, et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Varela, Polo, et al., 2016), which is similar to reports from Italy (18.8%) (Fusco et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As for HAstV, up to 20.8% of samples (mussels and clams) in Italy showed contamination with this agent (Fusco et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe presence of multiple viruses in shellfish is not uncommon (Le Guyader et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). We describe the coexistence of NoV GI and NoV GII in 3.9% of the samples analyzed. We also identified up to four viruses in the same sample, suggesting that the coexistence of different species, genotypes, and genogroups is common in our country, as described in oyster samples in Brazil (Do Nascimento et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the reports describing NoV disease peaks in the rainy or winter season (Ludwig-Begall et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), we did not identify any seasonality for NoV GI, NoV GII, RV, SaV, or HAstV. Although Ecuador does not have well-defined seasons, dry and rainy periods are usually demarked during the year. We did not identify associations between these seasons and most of the viruses detected. This may be attributed to the short sampling period considered in our study; longer sampling periods will be required in future studies to better characterize the seasonality of enteric viruses in our country. In contrast to previous reports (Tao et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), we found an association between HAdV and dry season. While a lack of HAdV seasonality was reported in shellfish in Brazil (Do Nascimento et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), a seasonality has been described based on stool sample analysis in the Northern region of this country with a higher prevalence of HAdV during summer and spring (Do Nascimento et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), similar to our findings.\u003c/p\u003e \u003cp\u003eThe concentration of human enteric pathogens (viruses and bacteria) in bivalves is generally the result of contamination of the environment in which they live, and this may be caused by wastewater (Hassard et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Mangroves represent a special ecosystem and pollution assessment studies have documented fecal contamination in Ecuadorian mangroves (Pern\u0026iacute;a et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and rivers (Vinueza et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In Quito, the capital of Ecuador, 171\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e of wastewater is produced per year and less than 7% is treated. Not only the wastewater from Quito but from all of Ecuador is collected by several rivers before reaching the Pacific Ocean (Guerrero-Latorre et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The results obtained in our study underscore these previous reports, although we did not analyze mangrove water or shellfishes collected directly for mangroves to fully support this assumption. Still, efforts to ensure mangrove water quality should be reinforced in our country.\u003c/p\u003e \u003cp\u003eBlack shellfish are commonly consumed raw in typical Ecuadorian dishes such as ceviche, posing a risk to the consumer, as described elsewhere (Orden-Mej\u0026iacute;a et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Post-harvest purification methods, including placing shellfish in clean tanks with purified water before commercialization, are commonly used to remove pathogens or reduce their concentration in shellfish (Yang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, this process is not as effective at removing viruses as it is at removing bacteria (Sharp et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Proper cooking of seafood (90 degrees Celsius over 90 seconds) is a better strategy to reduce the risks, since high temperatures are effective at inactivating viruses (Bozkurt et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this study is the first to identify viral genetic material from black shellfish sold in local markets in Ecuadorian cities. Our findings highlight the need to strengthen assessment tools for the timely identification of viral pathogens in commercial shellfish for risk assessment of food-transmitted diseases. In the future, larger sampling, and including additional sampling areas, as well as genotyping analyses will be needed to better characterize the prevalence and genetic diversity of human pathogens among black shellfish.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eDuring 2021, five enteric viruses (NoVGI and GII, HAdV, HAstV, SaV and RV) were detected from bivalves collected from sea food markets on the Ecuadorian main land, while only HAdV was identified among oysters from natural environment in the Galapagos Islands. Furthermore, most of these bivalves did not meet national or international food safety criteria regarding \u003cem\u003eE. coli\u003c/em\u003e enumeration. These results demonstrate the circulation of viral pathogens within bivalves, water and the Ecuadorian population, highlighting the need to implement surveillance programs to adequately monitor these potential public health risks.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eConceptualization: Lorena Mej\u0026iacute;a; Methodology: Mery Ulloa Gonzalez, Eloisa Hasing, Juan Daniel Mosquera, Lorena Mej\u0026iacute;a; Formal analysis and investigation: Mery Ulloa Gonzalez, Lorena Mej\u0026iacute;a; Writing - original draft preparation: Mery Ulloa Gonzalez, Pablo Endara, Lorena Mej\u0026iacute;a; Writing - review and editing: Mery Ulloa Gonzalez, Eloisa Hasing, Juan Daniel Mosquera, Sonia Zapata, Lorena Mej\u0026iacute;a; Funding acquisition: Lorena Mej\u0026iacute;a.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by USFQ Collaboration Grants 2019 and the USFQ COCIBA Grant 2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003eThe funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBosch, A., Gkogka, E., Le Guyader, F. S., Loisy-Hamon, F., Lee, A., Van Lieshout, L., Marthi, B., Myrmel, M., Sansom, A., Schultz, A. C., Winkler, A., Zuber, S., \u0026amp; Phister, T. (2018). Foodborne viruses: Detection, risk assessment, and control options in food processing. \u003cem\u003eInternational Journal of Food Microbiology\u003c/em\u003e, \u003cem\u003e285\u003c/em\u003e, 110\u0026ndash;128. https://doi.org/10.1016/j.ijfoodmicro.2018.06.001\u003c/li\u003e\n\u003cli\u003eBourdett-Stanziola, L., Cuevas-Abrego, M., Ferrera, A., \u0026amp; A. Durant-Archibold, A. (2022). Rotavirus in Oysters, Lettuce, and Feces in Children with Diarrhea from Panama. \u003cem\u003eJournal of Advances in Microbiology\u003c/em\u003e, 16\u0026ndash;21. https://doi.org/10.9734/jamb/2022/v22i530459\u003c/li\u003e\n\u003cli\u003eBozkurt, H., D\u0026rsquo;souza, D. H., \u0026amp; Davidson, P. M. (2015). 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L. (2016). Prevalence and Genetic Diversity of Human Sapoviruses in Shellfish from Commercial Production Areas in Galicia, Spain. \u003cem\u003eApplied and Environmental Microbiology\u003c/em\u003e, \u003cem\u003e82\u003c/em\u003e(4), 1167\u0026ndash;1172. https://doi.org/10.1128/AEM.02578-15\u003c/li\u003e\n\u003cli\u003eVinueza, D., Ochoa-Herrera, V., Maurice, L., Tamayo, E., Mej\u0026iacute;a, L., Tejera, E., \u0026amp; Machado, A. (2021). Determining the microbial and chemical contamination in Ecuador\u0026rsquo;s main rivers. \u003cem\u003eScientific Reports\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(1), 17640. https://doi.org/10.1038/s41598-021-96926-z\u003c/li\u003e\n\u003cli\u003eWHO (Ed.). (2015). \u003cem\u003eWHO estimates of the global burden of foodborne diseases\u003c/em\u003e. World Health Organization.\u003c/li\u003e\n\u003cli\u003eYang, M., Zhao, F., Tong, L., Wang, S., \u0026amp; Zhou, D. (2022). Contamination, bioaccumulation mechanism, detection, and control of human norovirus in bivalve shellfish: A review. \u003cem\u003eCritical Reviews in Food Science and Nutrition\u003c/em\u003e, \u003cem\u003e62\u003c/em\u003e(32), 8972\u0026ndash;8985. https://doi.org/10.1080/10408398.2021.1937510\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Enteric viruses, bivalve, Norovirus, Rotavirus, Adenovirus","lastPublishedDoi":"10.21203/rs.3.rs-9296080/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9296080/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFood-related illnesses remain a major health concern worldwide, and more than one-fifth of them can be attributed to enteric viruses. Bivalve mollusks are recognized vectors due to their ability to concentrate pathogens and toxins present in the surrounding water of the environment in which they live, and because they are consumed raw or undercooked. In Ecuador, food contamination with viruses is a little explored area. Furthermore, only a small percentage of wastewater is treated before being discharged into the sea. Therefore, this descriptive study aimed to determine the presence of five enteric viruses in bivalves (mainly black shellfish) during the second semester of 2021.\u003c/p\u003e \u003cp\u003eWe analyzed 98 samples of bivalves from markets in 8 continental Ecuadorian cities and 3 wild mangrove oysters from Galapagos Islands using qRT-PCR to detect the enteric viruses: Norovirus genogroups I and II, human Adenovirus serotypes 40 and 41, Rotavirus A, human Astrovirus, and Sapovirus.\u003c/p\u003e \u003cp\u003eAt least one virus was detected in 69.3% of the samples, and 38.6% showed contamination with a single virus. Adenovirus was the most common (49.5%), followed by Norovirus genogroup I (20.8%). Two viruses were co-detected in 19.8% of the samples, being Rotavirus-Adenovirus the most common combination. Three viruses were detected in 8.9% of the samples. Seasonality was observed for adenovirus, with an increased detection occurring during the dry season.\u003c/p\u003e \u003cp\u003eOur findings demonstrate the presence of genetic material of human viruses in Ecuadorian bivalves during 2021, reflecting viral circulation within our population and a potential health risk that should be addressed.\u003c/p\u003e","manuscriptTitle":"Surveillance of enteric viruses in bivalves from Ecuador during the year 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-10 15:12:24","doi":"10.21203/rs.3.rs-9296080/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"34bceb0d-b200-499e-ab26-ba6e0ab47520","owner":[],"postedDate":"April 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T06:11:06+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-10 15:12:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9296080","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9296080","identity":"rs-9296080","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}